A fiber-segmentation algorithm for composites imaged using X-ray microtomography: Development and validation

This study proposes a new algorithm for three-dimensional segmentation of fibers in multi-directional fiber-reinforced composites (FRCs) imaged using X-ray microtomography (mu CT). The proposed algorithm uses synthetic fiber-templates and template matching to detect fibers in 2D. Detections are used to track individual fibers in 3D using a Kalman-filter estimator. Validation of the algorithm was performed using synthetic image stacks, which mimicked the quality and resolution of existing state-of-the-art X-ray systems. Segmentation of synthetic images revealed that the proposed algorithm estimates the total number of fibers, the 3D positions of fiber cross-sectional centroids, and fiber lengths with an error less than 7% when the image resolution is greater than 9 pixels per average fiber diameter. However, the segmentation algorithm was found to underestimate fiber cross-sectional areas due to beam-hardening artifacts. This study concludes by demonstrating the versatility of the algorithm on a multi-directional FRC imaged using X-ray mu CT.